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In this paper, a novel pilot-aided algorithm is proposed for the detection of integer frequency offset (IFO) in orthogonal frequency division multiplexing (OFDM) systems. By transforming the IFO into two new integer parameters, the proposed method can largely reduce the number of trial values for the true IFO. The two new integer parameters are detected using two different pilot sequences, a periodic...
Content-based image retrieval is a technology that is used to identify similar images based on their visual content. Relevant images are found by employing methods that rank images and show the top-ranked images. One important query pertaining to image retrieval methods is regarding as to how to rank the results. This paper proposes a new method based on an unsupervised Hopfield neural network that...
Feature extraction from each scale of an image pyramid to construct a feature pyramid is considered as a computational bottleneck for many object detectors. In this paper, we present a novel technique for the approximation of feature pyramids in the 2D discrete cosine transform (2DDCT) domain. The proposed method is based on a feature resampling technique in the 2DDCT domain, and exploits the effect...
A multimodal biometric system consolidates multiple biometric sources and mitigates the limitations of the unimodal biometric system. The consolidation of information can be done at various levels of fusion. In this paper, a normalization technique for score-level fusion based on a new anchor, which is computed from the raw score set, has been proposed. This new anchor is independent of the statistatical...
In this paper, we address the problem of estimating the two-dimensional (2-D) directions of arrival (DOA) of multiple signals, by means of a sparse L-shaped array. The array consists of one uniform linear array (ULA) and one sparse linear array (SLA). The shift-invariance property of the ULA is used to estimate the elevation angles with low computational burden. The source waveforms are then obtained...
In the field of image and data compression there is always a need for novel transform coding techniques promising improved reconstruction and reduced computational complexity. The usage of integer adaptation of the popular discrete cosine transform (DCT) with fixed quantization is prevalent in the field of video compression due to its ease of computation and acceptable performance. However, there...
Fingerprint image quality heavily influences the recognition rate for fingerprint identification/verification systems. A low-quality fingerprint image may consists of broken ridges, scars, smears, falsely conglutinated ridges, poor ridge and valley contrast, etc. In this paper, we propose a novel and effective three-stage scheme to enhance low-quality fingerprint images. The first-stage consists of...
Presently, there is an undeniable need for novel transform coding techniques promising improved reconstruction and reduced computational complexity in the field of image and data compression. Discrete Tchebichef transform (DTT), though possessing valuable properties like energy compaction, is a potentially unexploited polynomial-based orthogonal transform, compared to the much popular Discrete Cosine...
In this paper, a high secure approach for transmission of medical images over wireless channels is presented. In this approach, algorithms based on Chaos and Brahmagupta-Bhãskara (BB) equation are proposed for encryption and decryption of the medical images. and no lossy encoding is used for coding the encrypted medical images. Furthermore, turbo channel coding is proposed to correct the transmission...
Digital watermarking is a technique adapted to embed patient information as watermark with medical images to reduce storage and transmission overheads. A multiple-input multiple-output (MIMO) transmission scheme in which multiple antennas are used in both transmitter and receiver has emerged as one of the most significant technical breakthroughs in modern wireless communications. This paper presents...
In this paper, we present a novel approach to the problem of estimating and tracking the direction-of-arrival (DOA) of signals with known waveforms and unknown gains impinging on symmetric sparse subarrays. Unlike the conventional methods, which estimate the DOA based on the spatial signature of the signal with known waveform, the proposed method partitions the whole least square (LS) problem into...
The conventional soft-decision based noise estimation algorithms normally assume that noise exists, only when speech is absent. Consequently, the estimated noise spectra are not updated in the segments of speech presence, but only in those of speech absence. This assumption often results in several problems such as delay and bias of noise spectrum estimates. In this paper, we propose a solution by...
An accurate direction-of-arrival (DOA) estimation algorithm with sparse sensor array is proposed. By dividing the nonuniform linear sparse array (NLSA) into two uniform linear sparse arrays (ULSA), the subarray response vectors yield a property of rotational invariance in the estimation of rough DOA without ambiguity using the so-called generalized ESPRIT. According to the estimated rough DOA, the...
Signal sparsity is the fundamental requirement of compressive sensing (CS) techniques. In our previous work, a CS-based speech enhancement algorithm has been proposed. However, several issues concerning speech sparsity have not yet been thoroughly studied. In this paper, we focus on studying the following issues: (1) the sparsity of clean speech and audio signals; (2) the sparsity of various noise...
Signal direction-of-arrival (DOA) estimation using an L-shaped array of sensors configured by two uniform linear arrays (ULA) has been an active research topic in array signal processing. A simple but efficient DOA estimation method has recently been proposed by exploiting the L-shape array geometry and the cross-correlation information of sensor data. In this paper, the asymptotic variance of the...
Principal component analysis (PCA), well-known for its compaction capability and robustness against noise, is a widely used technique for face recognition. However, it has major drawbacks: (i) losing image details, (ii) having a large time complexity and (iii) suffering from adverse effect of intra-class pose variations. To overcome the last drawback in PCA, Fourier magnitude (FM-PCA) has been proposed...
Recently, compressive sensing (CS) has been intensively studied in the fields of applied mathematics and signal processing. However, its application to speech processing has not been well discussed. In this paper, we propose a compressive sensing method for noise reduction of speech and audio signals. The noise reduction problem is formulated in the theoretical framework of CS, as an ℓ1-minimisation...
This paper presents a new method of estimating the direction-of-arrival (DOA) for multiple signals using minimum redundancy linear sparse subarrays (MRLSS). The proposed method makes use of the array structure to obtain the extended correlation matrix that is constructed by Kronecker Steering Vectors (KSVs) of which each contains the ambiguous and unambiguous angle with a one-to-one relationship....
In this paper, a one-parameter eight-point orthogonal transform suitable for image compression is proposed. An algorithm for its fast computation is developed and an efficient structure for a simple implementation valid for all possible values of its independent parameter is proposed. It is shown that an appropriate selection of the values of the parameter results in a number of new multiplication-free...
In this paper, an efficient algorithm for fast computation of the conjugate symmetric sequency-ordered complex Hadamard transform (CS-SCHT) of any length that is a power of two is proposed using the Kronecker product. Since the CS-SCHT matrix is factored into a product of sparse matrices, the resulting structure for the algorithm is very attractive for implementation and similar to that of the well-known...
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